Instructions to use dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Math-1.5B") model = PeftModel.from_pretrained(base_model, "dada22231/d9b72381-1ad7-4fa7-9d6b-670f1c0cfa90") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbb7b1c1b2d0d46ae9467373af4a249020b2ec4e927d40512cc0223e8cbbac96
- Size of remote file:
- 6.84 kB
- SHA256:
- a14ea3eaa48e21d3ec7c7005599bd143865cd3c71042e3bd9b227a840a30bb3c
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